scholarly journals A Fast Motion Parameters Estimation Method Based on Cross-Correlation of Adjacent Echoes for Wideband LFM Radars

2017 ◽  
Vol 7 (5) ◽  
pp. 500 ◽  
Author(s):  
Yi-Xiong Zhang ◽  
Ru-Jia Hong ◽  
Cheng-Fu Yang ◽  
Yun-Jian Zhang ◽  
Zhen-Miao Deng ◽  
...  
Keyword(s):  
Cross Correlation ◽  
Estimation Method ◽  
Parameters Estimation ◽  
Fast Motion ◽  
Motion Parameters

scholarly journals A Fast Motion Parameters Estimation Method Based on Cross-Correlation of Adjacent Echoes for Wideband LFM Radars

2017 ◽  
Author(s):  
Yixiong Zhang ◽  
Rujia Hong ◽  
Cheng-Fu Yang ◽  
Yunjian Zhang ◽  
Zhenmiao Deng ◽  
...  
Keyword(s):  
Cross Correlation ◽  
Computational Cost ◽  
Estimation Method ◽  
Doppler Frequency ◽  
Parameters Estimation ◽  
Estimation Methods ◽  
Radar Systems ◽  
Isar Imaging ◽  
Motion Parameters ◽  
Wideband Radar

In wideband radar systems, the performance of motion parameters estimation can significantly affect the performance of object detection and the quality of inverse synthetic aperture radar (ISAR) imaging. Although the traditional motion parameters estimation methods can reduce the range migration (RM) and Doppler frequency migration (DFM) effects in ISAR imaging, the computational complexity is high. In this paper, we propose a new fast non-searching motion parameters estimation method based on cross-correlation of adjacent echoes (CCAE) for wideband LFM signals. A cross-correlation operation is carried out for two adjacent echo signals, then the motion parameters can be calculated by estimating the frequency of the correlation result. The proposed CCAE method can be applied directly to the stretching system, which is commonly adopted in wideband radar systems. Simulational results demonstrate that the new method can achieve better estimation performances, with much lower computational cost, compared with existing methods. The experimental results on real radar data sets are also evaluated to verify the effectiveness and superiority of the proposed method compared to the state-of-the-art existing methods.

Weak Transient Electromagnetic Radiation Signal Detection Method Considering the New Watershed Image Segmentation Algorithm

2019 ◽  
Vol 34 (03) ◽  
pp. 2054009
Author(s):  
Wenjun Huo ◽  
Peng Chu ◽  
Kai Wang ◽  
Liangting Fu ◽  
Zhigang Niu ◽  
...  
Keyword(s):  
Electromagnetic Radiation ◽  
Cross Correlation ◽  
Detection Efficiency ◽  
Signal To Noise Ratio ◽  
Estimation Method ◽  
Detection Methods ◽  
Signal To Noise ◽  
Long Distance ◽  
Transient Electromagnetic ◽  
Noise Ratio

In order to study the detection methods of weak transient electromagnetic radiation signals, a detection algorithm integrating generalized cross-correlation and chaotic sequence prediction is proposed in this paper. Based on the dual-antenna test and cross-correlation information estimation method, the detection of aperiodic weak discharge signals under low signal-to-noise ratio is transformed into the estimation of periodic delay parameters, and the noise is reduced at the same time. The feasibility of this method is verified by simulation and experimental analysis. The results show that under the condition of low signal-to-noise ratio, the integrated method can effectively suppress the influence of 10 noise disturbances. It has a high detection probability for weak transient electromagnetic radiation signals, and needs fewer pulse accumulation times, which improves the detection efficiency and is more suitable for long-distance detection of weak electromagnetic radiation sources.

scholarly journals Experimental Evaluation of PSO Based Transfer Learning Method for Meteorological Visibility Estimation

Atmosphere ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 828
Author(s):  
Wai Lun Lo ◽  
Henry Shu Hung Chung ◽  
Hong Fu
Keyword(s):  
Transfer Learning ◽  
Experimental Evaluation ◽  
Estimation Method ◽  
Image Features ◽  
Parameters Estimation ◽  
Image Feature ◽  
Support Vector ◽  
Learning Method ◽  
Feature Vectors ◽  
Visibility Estimation

Estimation of Meteorological visibility from image characteristics is a challenging problem in the research of meteorological parameters estimation. Meteorological visibility can be used to indicate the weather transparency and this indicator is important for transport safety. This paper summarizes the outcomes of the experimental evaluation of a Particle Swarm Optimization (PSO) based transfer learning method for meteorological visibility estimation method. This paper proposes a modified approach of the transfer learning method for visibility estimation by using PSO feature selection. Image data are collected at fixed location with fixed viewing angle. The database images were gone through a pre-processing step of gray-averaging so as to provide information of static landmark objects for automatic extraction of effective regions from images. Effective regions are then extracted from image database and the image features are then extracted from the Neural Network. Subset of Image features are selected based on the Particle Swarming Optimization (PSO) methods to obtain the image feature vectors for each effective sub-region. The image feature vectors are then used to estimate the visibilities of the images by using the Multiple Support Vector Regression (SVR) models. Experimental results show that the proposed method can give an accuracy more than 90% for visibility estimation and the proposed method is effective and robust.

Cramer-Rao bounds for micro-motion parameters estimation in coherent laser detection

2017 ◽  
Vol 46 (7) ◽  
pp. 706002
Author(s):  
郭力仁 Guo Liren ◽  
胡以华 Hu Yihua ◽  
王云鹏 Wang Yunpeng
Keyword(s):  
Parameters Estimation ◽  
Laser Detection ◽  
Micro Motion ◽  
Motion Parameters

scholarly journals Micro-Motion Dynamics and Shape Parameters Estimation Based on an Infrared Signature Model of Spatial Targets

Electronics ◽  
2019 ◽  
Vol 8 (7) ◽  
pp. 755 ◽  
Author(s):  
Dongya Wu ◽  
Huanzhang Lu ◽  
Bendong Zhao ◽  
Junliang Liu ◽  
Ming Zhao
Keyword(s):  
Radiation Intensity ◽  
Infrared Radiation ◽  
Estimation Method ◽  
Optimization Techniques ◽  
Parameters Estimation ◽  
Geometrical Shape ◽  
Infrared Signature ◽  
Micro Motion ◽  
Periodic Fluctuations ◽  
Motion Dynamics

Infrared imaging is widely applied in the discrimination of spatial targets. Extracting distinguishable features from the infrared signature of spatial targets is an important premise for this task. When a target in outer space experiences micro-motion, it causes periodic fluctuations in the observed infrared radiation intensity signature. Periodic fluctuations can reflect some potential factors of the received data, such as structure, dynamics, etc., and provide possible ways to analyze the signature. The purpose of this paper is to estimate the micro-motion dynamics and geometry parameters from the observed infrared radiation intensity signature. To this end, we have studied the signal model of the infrared radiation intensity signature, conducted the geometry and micro-motion models of the target, and we proposed a joint parameter estimation method based on optimization techniques. After analyzing the estimation results, we testified that the parameters of micro-motion and geometrical shape of the spatial target can be effectively estimated by our estimation method.

Target Motion Parameters Estimation in Forward Scatter Radar

2020 ◽  
Vol 56 (1) ◽  
pp. 226-248 ◽  
Author(s):  
Nertjana Ustalli ◽  
Debora Pastina ◽  
Pierfrancesco Lombardo
Keyword(s):  
Parameters Estimation ◽  
Target Motion ◽  
Forward Scatter ◽  
Scatter Radar ◽  
Motion Parameters
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